Ирина Карловна Васильева

KhAI - Aerospace university

The chapter considers some aspects of processing multichannel remote sensing images using trained neural networks

Метою українсько-французького проекту в рамках програми «Дніпро», що виконувався в 2021 році (саме його результати викладені у даному розділі), була розробка методів та алгоритмів ефективної обробки зображень на основі машинного навчання та інших сучасних засобів для багатоканальних даних дистанційного зондування. Дослідження знаходяться на перетин...

The reliability of remote sensing data classification is significantly affected by the quality of images and the efficiency of algorithms and methods used at all stages of their processing. At the same time, the complementarity of satellite data and the results of aerial photography from UAVs opens up wide opportunities for their joint use in order...

Abstract—The results of verification of the method for predicting the classification accuracy for three-channel remote sensing images are presented. This study is carried out based on pixel-by-pixel classification according to the maximum likelihood criterion. As a criterion for classification accuracy, the weighted total probability of correct rec...

Classification accuracy of remote sensing data depends on many factors including level of distortions if lossy compression is applied to original data. However, it is difficult to predict what compression ratio or characteristics of distortions have to be provided in order to ensure classification accuracy reduction due to lossy compression is appr...

Acquired images often have a large size while there can be limitations on communication line capacity and/or storage memory. Then, there is a need to compressed them. If lossy compression is applied, compressed images should have quality enough high for solving the tasks of their further processing as segmentation, classification, object detection....

Lossy compression of remote sensing data has found numerous applications. Several requirements are usually imposed on methods and algorithms to be used. A large compression ratio has to be provided, introduced distortions should not lead to sufficient reduction of classification accuracy, compression has to be realized quickly enough, etc. An addit...

In this paper, we consider a problem of lossy compression of three-channel or color images with application to remote sensing. The main task of such a compression is to provide a trade-off between compression ratio and quality of compressed data that should be appropriate for solving the basic tasks as classification of sensed terrains, object dete...

The goal of our studies in 2018–2020 has been design of approaches and methods for automated processing of remote sensing (RS) and other types of data acquired by different existing imaging systems most of which are multichannel.

Lossy compression is widely used to decrease the size of multichannel remote sensing data. Alongside this positive effect, lossy compression may lead to a negative outcome as making worse image classification. Thus, if possible, lossy compression should be carried out carefully, controlling the quality of compressed images. In this paper, a depende...

A method for predicting probability characteristics for algorithms of supervised classification of multichannel images is proposed. Implementation of quasi-Bayesian image recognition strategy in conditions of incomplete a priori information about a satellite image is considered. Total weighted probability of correct class recognition is taken as a...

A task of classification of multichannel remote sensing images compressed in a lossy manner is considered. It is recalled that lossy compression usually leads to reduction of classification accuracy both in aggregate and for particular classes. Distortions due to compression are characterized by visual quality metric desired values of which can be...

The subject of this study is the pixel-by-pixel controlled classification of multichannel satellite images distorted by additive white Gaussian noise. The paper aim is to study the effectiveness of various methods of image classification in a wide range of signal-to-noise ratios; an F-measure is used as a criterion for recognition efficiency. It is...

A post-classification processing technique for multi-channel images that includes three stages is proposed. The purpose of the first stage is to correct decisions of pixel-by-pixel classifiers based on estimates of classes' posterior probabilities. At the second stage, a logical convolution of the classification layers is performed which makes it p...

The subject matter of the article is the methods of automatic clustering of remote sensing data under conditions of a priori uncertainty regarding the number of observed object classes and the statistical characteristics of the signatures of classes. The aim is to develop a method for approximating multimodal empirical distributions of observationa...

The subject matter of the article are the methods of local spatial post-processing of images obtained as a result of statistical per-pixel classification of multichannel satellite images distorted by additive Gaussian noise. The aim is to investigate the effectiveness of some variants of post-classification image processing methods over a wide rang...

The subject matter of the article is the methods of morphological spatial filtering of images in pseudo-colors obtained as a result of statistical segmentation of multichannel satellite images. The aim is to study the effectiveness of various methods of post-classification image processing in order to increase the probability of correct recognition...

The subject matter of the article are the processes of forming of objects’ attribute features analytical descriptions for solving applied problems of statistical recognition of objects’ images on multi-channel images. The goal is to develop a multicomponent mathematical model for representing statistical information about the summation of geometric...

Methods for detecting contour points of objects on segmented images formed by the method of statistical recognition of multichannel data are proposed. Algorithms for linking of adjacent isolated points of the contour of the selected area using distance criteria have been developed. The obtained arrays of points belonging to the outer contour allow...